OnMobile Global Data Analyst Interview Questions and Answers

Python and SQL Questions (Easy to Medium)

Q1. Project Work Discussion
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Q2. SQL Coding (Can be with an online compiler)
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Q3. Python Coding (Can be with an online compiler)
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Q4. PySpark Coding (All the coding answers have to be submitted to the interviewer)
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Q5. PySpark Joins, and Databricks, and Vanilla Spark difference
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Q1. SQL 2 Questions (Easy to Medium) (Maybe on the compiler)
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Q2. Python (Easy) (Maybe on compiler)
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Q3. Scenario-based questions on the project
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Based on your job description coding questions will be asked in different categories. If you are able to manage time. It is easy to crack

Q1. Optimization techniques in pyspark
Ans. 
Optimization techniques in pyspark involve partitioning, caching, and using efficient transformations.
• Partitioning data to distribute workload evenly

• Caching frequently accessed data to avoid recomputation

• Using efficient transformations like map, filter, and reduce

• Avoiding unnecessary shuffling of data
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Q2. Few coding questions. Find the first unique character in string
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Q1. It is bit difficult for me. Mention your work experience
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1 python hands on question and 20 SQL based questions

Q1. Azure Databricks
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Q2. Azure Data Factory
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Q1. SQL handson questions
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Q2. Python hands on question
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Asked few Python questions

Q1. Spark Architecture
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Q1. Basics of Python SQL Cloud and new technologies like Spark would be an advantage Panel was quite interactive and supportive
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Q2. Code based on arrays and lists sorting
Ans. 
Sorting arrays and lists of strings
• Use built-in sorting functions like sorted() or sort()

• Specify the key parameter to sort by a specific element in the strings

• Use reverse=True to sort in descending order
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Q1. Much into the project that I have worked upon, data structures, code based on arrays and time complexity
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There was a question which say, write the string in the reverse order.

Q1. What are your strengths and weakness.
Ans. 
My strengths include strong analytical skills and attention to detail. My weakness is that I can be overly critical of my own work.
• Strength: Strong analytical skills

• Strength: Attention to detail

• Weakness: Overly critical of my own work
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Q2. Tell me about yourself
Ans. 
I am a data analyst with experience in analyzing and interpreting complex data sets to drive business insights.
• Proficient in SQL, Python, and Excel for data analysis

• Skilled in data visualization using Tableau and Power BI

• Experience in conducting statistical analysis and creating predictive models

• Strong problem-solving and critical thinking skills

• Effective communication and presentation skills

• Ability to work collaborati
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